Mollifying Realistic Image Synthesis for Time Constrained Rendering

• Applicant: Professor Dr.-Ing. Carsten Dachsbacher
• Subject Area: Image and Language Processing, Computer Graphics and Visualisation, Human Computer Interaction, Ubiquitous and Wearable Computing
• Term: from 2016 to 2021
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 323377784

Realistic image synthesis, or rendering, is a key problem in computer graphics with numerous application areas, from digital entertainment to architecture and industrial design. The goal of most previous rendering algorithms is to converge to the ground truth solution as quickly as possible with increasing computation time. Computation typically continues until desired quality criteria are met, but the desired computation time is not an input to the renderer. In contrast to this, in this project we consider the problem to obtain the best possible approximate solution under a given time constraint. A key idea is to achieve this by modifying the rendering problem at hand, that is the scene and the light transport simulation including image reconstruction, to obtain easier problems. This is often called "mollification". Mollification allows us to achieve better approximations of the desired image within a given time budget. Solving the mollified problem may in general not converge to the ground truth, but it will provide a better approximation given a limited time compared to solving the original problem. We believe this problem statement is highly relevant in application scenarios where the user cannot be expected to simply wait for an arbitrary amount of time until a simulation provides acceptable results. For example during interactive modeling or design, it is much more useful for users to specify a given amount of time they are willing to wait. Our proposed techniques attempt to deliver the best possible approximate solution in this time frame. In this project we will develop a theoretical framework for mollification, and practical algorithms to demonstrate its benefits.

• DFG Programme: Research Grants
• International Connection: Switzerland
• Partner Organisation: Schweizerischer Nationalfonds (SNF)
• Co-Investigator: Professor Dr. Matthias Zwicker